Deep Image Deblurring for Non-Uniform Blur: a Comparative Study of Restormer and BANet

Deep Image Deblurring for Non-Uniform Blur: a Comparative Study of Restormer and BANet

deep learning, blur attention, restormer, image deblurring, non-uniform

Image blur is one of the common degradations on an image. The blur that occurs on the captured images is sometimes non-uniform, with different levels of blur in different areas of the image. In recent years, most deblurring methods have been deep learning-based. These methods model deblurring as an imageto-image translation problem, treating images globally. This may result in poor performance when handling non-uniform blur in images. Therefore, in this paper, the author compared two state-of-the-art supervised deep learning methods for deblurring and restoration, e.g. BANet and Restormer, with a special focus on the non-uniform blur. The GOPRO training dataset, which is also used in various studies as a benchmark, was used to train the models. The trained models were then tested on the GOPRO testing test, the HIDE testing set for cross-dataset testing, and GOPRO-NU, which consists of
specifically selected non-uniform blurred images from the GOPRO testing set, for the non-uniform
deblur testing. On the GOPRO testing set, Restormer achieved an SSIM of 0.891 and PSNR of 27.66 while BANet obtained an SSIM of 0.926 and PSNR of 34.90. Meanwhile, for the HIDE dataset,
Restormer achieved an SSIM of 0.907 and PSNR of 27.93 while BANet obtained an SSIM of 0.908 and PSNR of 34.52. Finally, on the non-uniform blur GOPRO dataset, Restormer achieved an SSIM of
0.911 and PSNR of 29.48 while BANet obtained an SSIM of 0.935 and PSNR of 35.47. Overall, BANet
shows the best result in handling non-uniform blur with a significant improvement over Restormer.

Made Prastha Nugraha, Laksmita Rahadianti

http://dx.doi.org/10.21609/jiki.v17i2.1274

Faculty of Computer Science Universitas Indonesia

2024-06-04

Sri Wahyuni

e-ISSN : 2502-9274 printed ISSN : 2088-7051

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Jurnal Ilmu Komputer dan Informasi (Journal of Computer Science and Information)